DATASCI 447 Lecture 16: Variational Autoencoders

Administrative Stuff

THE GENERATIVE GOAL

We want to create a coherent space that we can sample from to produce images of dogs with high probability.

The problem: pixel space is enormous. A 64×64×3 image lives in \(\mathbb R^{64 \times 64 \times 3}\).

Almost all of that space is garbage — random static, melted faces, impossible textures. The set of “images that look like dogs” is a tiny, thin manifold winding through this vast space.

THE GENERATIVE GOAL

THE GENERATIVE SOLUTION

Project high-dimensional images down to a low-dimensional code vector in a simple space that uniquely maps back to the image.

Do it so that:

• Nearby codes → similar images

• We can sample new codes to generate new images

THE GENERATIVE SOLUTION

THE GENERATIVE SOLUTION

THE GENERATIVE SOLUTION